# R Tutorial

__Statistical Analysis__ | __Tutorial Main Menu__ | __A____pplying R to Political Science__

# Section 5: Statistical Analysis Part 2

### ANOVAS in R

In Figure 5-1 we will define three separate groups with 7 separate observations per group. Then, we will use **n** and **group** to combine the groups into vectors.

**n =rep(7, 3)** and **group =rep(1:3, n)** are vectors.

**Figure 5-1**

The **tmp = tapply(y, group, stem)** code is used to summarize the data by determining the decimal point locations**. **If the data contains all whole numbers then the output(on the right side of the vertical lines) would display zero's.

** **

**Figure 5-2**

The **tmpfn** function is a temporary function to show the overall summary of the 3 groups of data by displaying the **sum**, **mean**, **variance** and the value of **n**.

**Figure 5-3**

This is the summary of the information listed in Figure 5-4.

**Figure 5-4**

This code displays the ANOVA table into the R console.

**Figure 5-5**

### Frequency Distribution

We can create frequency distributions by manipulating a current dataset or by creating a new one.

Lets say we wanted to see how many students in a sample group liked blue. In this example we will be creating a boxplot to display the data. In Figure 5-6, we first import the dataset sample, which displays the ID, Color and Gender of the group.

**Figure 5-6**

In the code, we defined the 4 colors that were given in the sample(blue, green, red and white). We also have yellow as a category to show what the graph looks like when there is a color that no one chose as their favorite.

**Figure 5-7**

Once the graph is labeled, colored, and scaled to the appropriate range, it will look like Figure 5-8 below.

**Figure 5-8**